Experimental Characterization of Thermal Conductivity with a New Compact Hot-Box Prototype

Abstract

In this study, a new compact “hot-box” prototype with a volume of 0.602 m³ has been designed, instrumented, and implemented to experimentally characterize the thermal conductivity of specimens measuring 25 cm × 25 cm, with the thickness of the specimen varying up to a maximum of 10 cm. The prototype features a novel design aimed at enhancing flexibility and speed in changing specimens, thereby reducing downtime when testing different materials. It requires minimal space and incurs low development and maintenance costs. To validate the prototype’s functionality for measuring thermal conductivity, an oak wood specimen with a thickness of 3.81 cm was experimentally tested. The results indicate that the control system maintains key parameters under steady-state conditions for a significant duration. The thermal conductivity obtained for the oak wood specimen is 0.1695 W/m·K, with an expanded uncertainty of 0.0183 W/m·K for a 95% confidence interval.

1. Introduction

In the energy transition, buildings are considered a low-carbon-emission energy system. In the current context, residential and commercial buildings are responsible for consuming one third of the electricity produced globally and generating 17% of the emissions [1]. Based on these characteristics, buildings represent a key target for improving energy efficiency, environmental sustainability, construction phases, and financial viability. Buildings are, therefore, undergoing a process of adaptation to meet the urgent need for efficient and sustainable building systems, seeking a balance between environmental and financial considerations. This necessity has driven the construction industry, research institutes, and universities to explore alternatives for optimizing the energy performance of buildings in an environmentally friendly and efficient manner.

Thermal performance is fundamental to meet the new standard requirements in building energy. Therefore, the thermal characteristics of each component of the building envelope must be studied from energy and environmental points of view.

The materials used in the building envelope and interior are directly correlated with energy efficiency, indoor thermal comfort, lifecycle performance, and financial balance. Thus, the mechanical, thermal, and acoustic properties of the materials used play a fundamental role in developing construction solutions. In this regard, measuring these parameters ensures a better understanding of how materials influence the energy efficiency of construction systems. In the current scenario, the integration of new materials derived from agricultural [2,3,4] and industrial [5] waste is becoming increasingly popular in construction systems. These new materials are used to make insulation panels and fiber-reinforced composites for cement and bricks. Insulation panels based on various recycled agricultural waste provide alternative construction materials using low technology compared to traditional insulation.

The Dominican Republic is in the Caribbean Sea and has a tropical climate [6]. Agriculture is a key sector of the economy, which generates a large amount of agricultural waste, particularly rice husks, sugarcane bagasse, coconut fiber, beans, and cocoa shells. The production of insulation panels from these residues and their integration into the local construction system contributes to reducing the environmental impact, revaluing these materials, and minimizing costs. In that sense, the characterization of thermal properties is crucial for the appropriate use of insolation panels. Thermal conductivity is a fundamental parameter for calculating the thermal transmittance of construction materials, thus providing a benchmark that helps classify the insulation level of a material.

Currently, different instrumental methods exist for measuring thermal conductivity, which can be classified into two main categories: steady-state and transient measurement techniques [7].

Steady-state techniques include hot-box methods (HBMs) and heat-flow meters (HFMs), while transient techniques are associated with hot wire and hot disks. However, in developing countries, the use of commercial techniques is almost prohibited. Consequently, there is an urgent need to develop alternative methods for measuring thermal conductivity that are more flexible, accessible, and less expensive than the currently available methods, even in a prelaminar fashion [8].

In general, commercial equipment that is used to measure thermal conductivity has prohibitive costs (for example, equipment such as hot disk instruments), limiting or preventing its availability in developing countries.

In the case of the hot-box method, the ISO 8990:1994 [9] and ASTM-C518 [10] standards focus on characterizing thermal transmittance for construction material using the hot-box methodology, which is classified into two types based on experimental techniques: a guarded hot box and a calibrated hot-box. In both cases, for large specimens with a minimum dimension of 1 m × 1 m, the specimen is placed between the hot and cold chambers. In the guarded hot box, heat flux is measured directly with a heat-flux meter on the surface of the specimen. It employs a guarded unit to ensure heat is moved only through the test specimen to minimize losses, and the thermal load in a hot chamber is provided using a control system. In the calibrated hot box, a guard unit is not used; heat flux is indirectly determined by comparing it with a calibrated reference. The guarded hot box is applied for small specimens compared with the calibrated hot box. In addition, the guarded apparatus has been used more frequently in the literature as they are more accurate.

The main constraints of the hot-box methods that are based on “Industrial Standard” ISO or ASTM are identified as follows: the high cost of construction, significant laboratory space, high maintenance costs, structural complexity of the hot chamber, long testing durations, and the high energy consumption required [11]. According to Alqahtani et al., a single test conducted in an ASTM-certified laboratory could cost in the range of USD 6000 to USD 20,000 per specimen, and construction of a validated hot box under standards could cost up to USD 1,000,000 [12,13]. Additionally, the use of a hot box by certified standards requires a technician with a solid background to understand and operate the technology.

In the specialized literature, extensive efforts have been made to develop alternative methodologies for determining thermal conductivity using the approach of simple hot-box apparatus, a novel innovation that contributes to the preliminary calculation of thermal conductivity, as demonstrated by the following studies.

The thermal transmittance of a wall was evaluated by Meng et al. (2015) using a simple hot box–heat-flow meter method [14]. The specimen was a wall with a structure of one 240 mm insulation brick layer and two 20 mm plaster layers. The hot box had an exterior volume of 0.243 m³ (900 mm × 900 mm × 300 mm). The apparatus wall was built with a 15 mm wood composite board exterior and 25 mm rubber sponge plate with a thermal conductivity of 0.034 W/m·K. It was concluded that the experimental error of the wall’s thermal transmittance was 5.97% relative to the reference value. Sassine et al. (2017) [15] carried out an experiment to determine the thermal properties of masonry walls in old buildings in northern France. The masonry wall had dimensions of 0.06 m × 0.11 m × 0.22 m and was completely instrumented with thermocouples [15]. The hot-box method was used to control the thermal load on one surface of the wall while the other surface of the wall was open to the environment (cold chamber).

A small piece of hot-box apparatus was developed by Buratti et al. (2016 and 2018) at the University of Perugia (Italy) to measure thermal conductivity using two different methods: the hot-box method and the heat-flux method [16,17]. The apparatus had a volume of 0.4418 m³ (0.94 m × 0.50 m × 0.94 m) and was used as a hot chamber. The chamber wall was constructed with a sandwich structure consisting of two wood panels with a thickness of 2 cm surrounding a middle layer of polyurethane foam with a thickness of 20 cm. The cold chamber was controlled by the laboratory environment using commercial air conditioning. They used the specimen of foam polyurethane, polistyrol, polystyrene, and wood with dimensions of 0.3 m × 0.3 m for calibration and validation of the apparatus. The maximum temperature fluctuations on the surface of the specimen for the hot chamber and the cold chamber were reported to be 0.6 °C and 0.4 °C, respectively.

An experiment was conducted by Barbaresi et al. (2021) at the University of Bologna (Italy) to evaluate the thermal conductivity of materials using an innovative, low-cost, and low-tech movable hot box (cube) with an approximate volume of 1 m³ [11]. The cube was used as a hot box, and the laboratory environment was used to simulate the cold chamber. The structure of the cube was made of five 18 mm oriented strand board (OSB) panels and insulated with 80 mm thick expanded polystyrene (EPS) panels. The experimental apparatus was validated using a sample of OSB and EPS with dimensions of 0.5 m × 0.5 m. It was found that the error was minimized throughout the test.

The development of an affordable hot-box calorimeter was carried out by Saad Alqahtani (2023) to determine the U-value of various 3D-printed building bricks [12]. The wall of the apparatus was built with one layer of expanded polystyrene (EPS) with a thickness of 100 mm and an exterior layer with a thickness of 6 mm thick of plywood. A mask wall made of EPS with a central hole was used to thermally separate the hot chamber and cold chamber. The specimen was supported by the mask with dimensions of 0.2 m × 0.2 m. The cold chamber was controlled by a refrigerated circulator to vary the temperature. It was found that the apparatus estimated the sample performance with very good accuracy, with the maximum error reported as 6%.

A low-tech hot box, labeled as the “approachable hot box (AHB)”, was developed by McCormick et al. (2023) to evaluate the thermal conductivity of homogeneous materials [13]. The main innovation of the apparatus was that it focused on temperature and humidity instead of thermal load input as the standard hot box. The apparatus consisted of a hot chamber and a receiving chamber. The receiving chamber was open to the environment and was used to monitor temperature and humidity. The hot chamber was equipped with a wire electrical heater (25 W) to supply the thermal load, a fan, an Arduino temperature sensor, and a humidifier. The AHB was structured with both chambers having an exterior layer of 51 mm polystyrene insulation foam and a single layer of 16 mm plywood. The thermal transmittance adopted in the calculations was set at 33.40 W/m²·K (R-0.17). Specimens of plywood and concrete with dimensions of 0.305 m × 0.305 m were used to validate the experiment. It was concluded that the apparatus slightly overpredicted the expected values, particularly for the plywood specimen, with the error decreasing as the temperature gradient of the specimen surfaces increased.

A novel experimental cell prototype for characterizing thermal conductivity based on the hot-box methodology is proposed in this study. The accurate measurement of thermal conductivity is essential for evaluating the suitability of materials in energy-efficient construction, particularly in the development of sustainable insulating materials. Traditional measurement methods, such as the guarded hot plate and the heat-flow meter, often require expensive equipment and controlled laboratory conditions, which can limit accessibility and flexibility in experimental setups. The proposed system is aimed to provide a more adaptable and cost-effective alternative while maintaining reliable measurement accuracy.

Three key stages were involved in the development of the experimental cell. First, a prototype was designed to create a controlled environment for thermal characterization. Next, a control system was implemented to regulate the thermal load, ensuring a stable temperature gradient between the hot and cold chambers. Finally, the prototype was instrumented with high-precision sensors to monitor temperature variations and compute the thermal conductivity of any tested specimen.

The new experimental cell was built with external dimensions of 81 cm (height) × 61 cm (width) × 122 cm (length), resulting in a total volume of 0.602 m³. The testing of specimens with a fixed surface area of 25 cm × 25 cm and a variable thickness of up to 10 cm is allowed. This versatility enables the evaluation of a wide range of materials, including conventional construction elements, bio-based composites, and recycled materials. To validate the prototype’s performance, a specimen made of oak wood—whose thermal conductivity has been extensively studied and verified by various laboratories—was used as a reference material.

This article is structured as follows: Section 1 presents the introduction and background of the study. Section 2 details the materials and methods used, including the experimental cell architecture, instrumentation, and control system design. Section 3 describes the equations used for calculating thermal conductivity. Section 4 focuses on the results obtained and their subsequent discussion. Finally, Section 5 presents the conclusions and future research directions.

2. Materials and Methods

The experimental cell was developed in the Sustainable Construction Laboratory (Santo Domingo, Dominican Republic) with the primary objective of characterizing the thermal conductivity of insulating panels made from both traditional materials and new materials derived from agricultural or industrial waste. A schematic of the experimental cell is presented in Figure 1, designed following several recommendations from the ISO-8990:1994 standard. It is important to note that the constructed prototype falls outside the full scope of the standard, which specifies a minimum specimen size of 1 m × 1 m. The proposed flexible design addresses laboratory space constraints, maintenance, and operational costs and improves the speed of test preparation.

2.1. Experimental Cell Architecture

A layered format was used to construct the experimental cell:

• The outer layer was composed of plywood with a thickness of 1.5 cm and a thermal conductivity of 0.13 W/m·K, forming the external enclosure.
• The intermediate layer was made of expanded polystyrene with a thickness of 20 cm, a density of 20 kg/m³, and a thermal conductivity of 0.0358 W/m·K.
• The inner layer was composed of hardboard sheets with a thickness of 1 cm and a thermal conductivity of 0.10 W/m·K.

The external envelope was fully sealed with lateral and top covers that fit together using embedded slots. The geometric dimensions of the cell prototype are listed in

Table 1. Geometry of the experimental cell.

Parameters	Dimensions (H × W × L)
Experimental cell (Prototype)	81 cm × 61 cm × 122 cm
Hot chamber	33 cm × 20 cm × 61 cm
Cold chamber	26 cm × 20 cm × 44 cm
Specimen carrier	75 cm × 60 cm × 10 cm

.

The prototype consists of two chambers, identified as the hot chamber and the cold chamber, with dimensions provided in Table 1. Both chambers were separated by a specimen holder, constructed with an outer layer of 1.5 cm plywood and an interior filled with expanded polystyrene to enhance insulation (Figure 1). Two functions are served by the specimen holder:

• The airflow between the hot and cold chambers is separated, ensuring both physical and thermal division.
• The specimen is held, ensuring direct contact between the circulating air in both chambers and the specimen surfaces (Figure 1).

The specimen holder consisted of two separate symmetrical pieces: one acting as the base and the other as the closure. The test specimen was placed in the center of the holder using machine slots in both the base and closure pieces. The holder was designed to accommodate panel specimens with dimensions of 25 cm × 25 cm × Z cm, where Z can vary up to a maximum thickness of 10 cm.

As shown in Figure 1, the specimen holder was integrated into the experimental cell enclosure through lateral sliding slots. This embedded coupling ensured a tighter seal and minimized heat losses between the chambers in accordance with the construction recommendations of the standard [9]. To install a specimen in the holder, the base piece was first assembled within the envelope. Then, the specimen was placed in the slot of the base piece. To compensate for possible sealing irregularities between the holder and the specimen, the lateral edges were covered with a thin elastomeric foam layer (3–5 mm thick), preventing potential air leaks between chambers and thermal bridging. Finally, the closure piece was inserted into the envelope to fully separate the chambers.

During the commissioning process, various insulation thicknesses for the intermediate layer were tested. The optimal thickness was determined using thermographic techniques, identifying thermal bridges and temperature distribution through infrared imaging, as shown in Figure 2. As can be illustrated in Figure 2, the atmosphere operation conditions of the prototype in the laboratory, where $ϵ$ is the emissivity, Máx, maximum temperature, Min, minimum temperature, Prom, average temperature. Additionally, the experimental cell was equipped with four wheels to facilitate easy mobility.

2.2. Instrumentation and Control

Thermal conductivity was determined from experimental measurements obtained under conditions close to steady-state operation. This approach ensured a uniform temperature distribution on the specimen surfaces over a period. The temperature gradient and uniformity of temperature distribution were achieved by creating artificial atmospheres within the hot and cold chambers.

In the hot chamber, the internal atmosphere was established by supplying a thermal load using an electric resistance array to heat the air. To ensure homogeneous airflow, an axial fan was positioned near the thermal resistance to force air circulation by convection. The heating elements were helical resistances, each with a resistance of approximately 96 Ω and a power rating of 100–125 W. The electrical power supply and fan speed were controlled by adjusting the supply voltage using a dimmer (

Table 2. Characteristics of measuring instruments.

Variables	Sensor	Range	Precision	Cost (USD)
Surface temperature	Type T	(−30, 250)°C	±0.5 °C	383
Heat flow	Thermopile	(−150, 150) kW/m2	7.7 mV/(W/cm2)	420

).

Inside the hot chamber, at 32 cm from the specimen and 22 cm from the fan, a 0.5 cm plywood vertical shield was installed to protect the specimen from internal radiation effects generated by the resistance and direct airflow. Additionally, the entire inner perimeter of the hot chamber was lined with a hardboard, a low-emissivity material, which helped mitigate radiation effects and prevented the expanded polystyrene layer from coming into direct contact with the thermal resistance.

To maintain steady-state operating conditions, a control system was required by the hot chamber to adjust the thermal load based on internal air temperature. Since the prototype’s hot chamber exhibited high thermal inertia, a control strategy was needed to optimize response time for each test. For this reason, a lead compensator with integral action was implemented to reduce steady-state error without significantly affecting settling time. A PWM-based thermal regulation system, using an array of electric resistances, was employed to control heat flux within the hot chamber, maintaining near-steady-state conditions.

In the cold chamber, the internal atmosphere was directly influenced by laboratory conditions, as it was open to the surrounding environment. Consequently, the air temperature was affected by the ambient conditions. To enhance control over the laboratory atmosphere, a dedicated space of 215 cm (width) × 300 cm (length) × 275 cm (height) was allocated, equipped with an air-conditioning system exclusively dedicated to the laboratory.

2.3. Measurement and Data Acquisition

Process monitoring was performed using surface temperature sensors and heat-flux thermopile sensors, which were fixed to the specimen surfaces. The sensors were connected to a LabJack T7-Pro data acquisition system, whose specifications are detailed in

Table 3. Equipment used in the experimental cell.

Equipment	Model	Characteristics	Cost (USD)
Datalogger	LabJack T7-Pro	14 analog inputs, Communication: USB, Ethernet802.11b/g WiFi speed: 16 bits	735
Axial fan		PWM, 12 Vcc, 0.26 A	22
Voltage regulator	Kira dimmer AC	Input: 0–120 Vac	27
Thermal resistance	helical wire	110–125 W AC	26
Energy meter	DROK 200123	22 kW, 9999 kWh	22
Hot-box architecture	Material + construction		800

.

To measure the surface temperature on the specimen in the hot chamber, five Type T surface thermocouples were used, distributed as follows:

• One thermocouple was placed at the center of the specimen.

Four thermocouples were positioned 15 cm from the center, at the north, south, east, and west coordinates (Figure 3).

This arrangement allowed the uniformity of temperature distribution to be analyzed. The heat-flux density was measured using two PHFS-01e thermopile-type heat-flux sensors (FluxTeq LLC, Blacksburg, VA, USA), which were mounted on the specimen surface. The sensor distribution is illustrated in Figure 3:

• One heat-flux sensor was placed at the center of the specimen.
• Another was located 15 cm south of the center.
• The specifications of these sensors are summarized in Table 2.
• On the cold chamber side, two Type T surface thermocouples were fixed on the specimen: one at the center and another 15 cm north of the center.

To manage thermal load control and monitor and store measured variables, a custom interface was developed using Python version 3.11. Data acquisition was performed at a sampling rate of one (1) second, and each test generated a data file containing all measured variables. Data processing and analysis were conducted using MATLAB 2022b.

3. Thermal Conductivity

Thermal conductivity was determined using Fourier’s principle for heat transfer through a material, assuming a unidirectional heat transmission, steady-state operation, and that the specimen’s properties remained unchanged along the direction of heat flow.

$$\lambda ={\displaystyle \frac{\left(\sum _{i=1¨}^n{\dot{q}}_{x,i}\right)dx}{\sum _{j=1}^n\left({\overline{T}}_{hot,j}-{\overline{T}}_{cool,j}\right)}}\left(\mathrm{W}/\mathrm{m}·\mathrm{K}\right)$$

(1)

The thermal conductivity model (λ) relates to the heat-flux density (${\dot{q}}_x$), the specimen thickness dx, the average temperature of the specimen’s hot surface (${\overline{T}}_{hot}$), and the average temperature of the specimen’s cold surface (${\overline{T}}_{cool}$).

To assess the reliability of the experiment, an uncertainty analysis was performed following the recommendations established in the Guide to the Expression of Uncertainty in Measurement (GUM) [18]. The propagation of uncertainty through the variables associated with thermal conductivity was estimated using the Taylor series expansion:

$$\lambda =f\left({\dot{q}}_x,dx, {\overline{T}}_{hot},{\overline{T}}_{cool} \right)$$

(2)

$${u^2}_{\lambda }=\sum _{i=1}^{n=4}{\left[{\displaystyle \frac{\mathsf{\partial }\lambda }{{\mathsf{\partial }x}_i}}\right]}^2{u}^2\left(x\right) x :\left\{{\dot{q}}_x,dx, {\overline{T}}_{hot},{\overline{T}}_{cool}\right\}$$

(3)

The combined uncertainty (ux) was calculated by integrating Type A and Type B uncertainties for each variable that contributed to λ.

$${u^2}_x=u_A^2+u_B^2$$

(4)

Type A uncertainty was estimated based on the repeatability of measurements using $u_A^2={\displaystyle \frac{S_x}{\sqrt{n}}}$. Type B uncertainty was associated with the manufacturing specifications of the measuring instruments. The expanded uncertainty inherent to the thermal conductivity for a 95% confidence level was calculated accordingly.

$$U_{\lambda }=\mp {k·\left(u_{\lambda }^2\right)}^{{\displaystyle \frac{1}{2}}}=\mp 1.96·{\left(u_{\lambda }^2\right)}^{{\displaystyle \frac{1}{2}}}$$

(5)

The frequency distribution of the uncertainty for thermal conductivity measurements is shown in Figure 4. The plot curve ensures that most of the calculated values fall within the 95% confidence interval (±1.96$\sigma$).

4. Results and Discussion

In this study, a new experimental cell prototype with a physical volume of 0.602 m³ was designed to measure the thermal conductivity of a specimen with a fixed area of 25 cm × 25 cm and a thickness of less than 10 cm, using the hot-box technique. The prototype was equipped with a thermal regulator to adjust the internal atmosphere of the hot chamber, generating a temperature difference across the specimen with the cold chamber. The atmosphere inside the cold chamber depends on the environmental conditions of the laboratory, which are controlled using a dedicated air-conditioning system.

To validate the prototype’s operation, an experimental test was conducted with an oak-based specimen with dimensions of 25 cm × 25 cm and a thickness of 3.81 cm. The oak sample was selected because it corresponded to a well-known construction material with extensively studied thermal properties. This selection facilitated the comparison of the experimental thermal conductivity value obtained with the new prototype against reference values reported by laboratories and studies in the literature.

The experimental process conducted with the prototype is illustrated in Figure 5. The total experiment duration was 1.5 h, corresponding to 5400 recorded readings. It is important to note that experimental measurements were recorded only after the hot chamber reached the target setpoint temperature of 70 °C established for this study. Figure 6a shows the temperature behavior captured by the sensors positioned at the center, south, west, north, and east of the oak specimen throughout the entire 1.5 h test. It was observed that the temperatures exhibited minimal fluctuations and remained close to the setpoint value (70 °C). The ambient laboratory temperature and the temperatures measured on the cold surface of the specimen are shown in Figure 6b. The laboratory temperature remained approximately constant at 21 °C, while the temperatures on the cold surface of the specimen displayed smooth lines without disturbances, with a central value close to 38 °C.

The measurements obtained from the heat-flux sensors positioned at the center and south coordinates of the oak specimen during the experiment exhibited rapid short-spectrum oscillations (Figure 6c). This behavior was reported in other studies [11,16], suggesting that it could be associated with transient phenomena caused by rapid fluctuations in the temperature differential due to small changes in the internal atmosphere of the hot chamber.

The thermal conductivity (Equation (1)) obtained from the average values of the main parameters recorded in each reading is shown in Figure 6d. Initially, the trend of the curve continuously decreased until it converged to an approximately constant value (Figure 6d). This behavior was expected according to the ISO-9869-1:2014 standard [19] and was observed in theoretical studies by other authors [11,20].

The total thermal conductivity was evaluated using the experimental measurements recorded under steady-state conditions during the test, totaling 2700 readings over 45 min. The average values for each reading of the main parameters associated with thermal conductivity are presented in Figure 7a. All average values of the hot and cold surface temperatures of the specimen remained close to constant conditions. The heat flux showed short oscillations with a central value of 134.03 W/m². The temperature difference between the hot and cold surfaces of the oak specimen remained approximately 30.18 °C. The test characteristics are detailed in

Table 4. Main parameters of the test to evaluate thermal conductivity.

Parameters	Values
Thickness of specimen [cm]	3.81
Steady-state sample [min]	45
Set point for hot chamber temperature [°C]	70
Temperature difference between the hot and cold surfaces of the specimen [°C]	30.181
Average temperature of the hot surface of the specimen [°C]	68.470
Average heat flux $\dot{q}$ [W/m2]	134.03
Average thermal conductivity [W/m·K]	0.1695 ± 0.0183

. In Figure 7b, it was observed that the thermal conductivity calculated using the average values of the specimen under steady-state conditions remained within a narrow control range, with a difference between the minimum and maximum values of 0.0580 W/m·K.

The total thermal conductivity value obtained was 0.1695 W/m·K, with an associated uncertainty of ±0.0183 W/m·K for a 95% confidence interval. This thermal conductivity value was consistent with values reported by other laboratories for an oak specimen [21,22,23].

Additionally, a laboratory validation test was conducted to determine the thermal conductivity of the oak specimen. Following the ASTM C518-17 standard [24], thermal conductivity and volumetric specific heat were evaluated using the Hot Disk TPS 500 device—Figure 8a [25], measured with certified commercial equipment. Two specimens of the same material, approximately 20 cm × 8 cm in size and 3.8 cm thick, were used. The sensor was placed between two halves of the sample, with a weight applied to ensure proper contact. The sensor emitted a thermal signal and recorded the temperature variation using circular sensors. The device directly provided the measured values, which were 0.1695 W/m·K for thermal conductivity and 0.00706 MJ/m³K for volumetric specific heat—Figure 8b. The results from the equipment indicated a thermal conductivity of 0.170 W/m·K, a value very close to that obtained experimentally. The average values of the main parameters for the specimen under steady-state conditions and the total thermal conductivity are summarized in Table 4.

5. Conclusions

In this study, a new experimental cell prototype with a volume of 0.602 m³ was developed to characterize the thermal conductivity of specimens with a fixed area of 25 cm × 25 cm and variable thickness up to 10 cm. To validate the prototype’s operability, a 3.81 cm thick oak wood specimen was tested.

The main findings are summarized as follows:

• The PWM-based thermal regulator, designed to adjust the internal atmosphere of the hot chamber by supplying a heat flux, performed well, maintaining the air temperature close to steady-state conditions.
• The temperature difference between the hot and cold surfaces of the specimen remained close to 30.18 °C in the steady-state regime identified during the experimental test.
• A thermal conductivity of 0.1695 W/m·K was obtained, with an expanded uncertainty of ±0.0183 W/m·K at a 95% confidence interval. The experimental value was confirmed by certified commercial equipment (Hot Disk TPS-500S). In addition, the obtained thermal conductivity value fell within the reference range reported by other laboratories using an oak wood specimen.

The developed prototype offered several advantages, including the ability to provide preliminary thermal conductivity values with increased flexibility and faster testing times for different specimens while occupying less laboratory space and maintaining a cost-effective setup. Compared to traditional methods, this system allowed greater adaptability in testing diverse materials, making it particularly useful for studies on sustainable construction materials.

Despite its promising performance, the prototype presented some limitations, such as the potential need for improved temperature stabilization mechanisms and the evaluation of samples with greater thicknesses. Future work should focus on refining the system to reduce measurement uncertainty and enhance automation in data acquisition.

Moreover, this prototype represented a valuable tool for characterizing the thermal properties of bio-based and recycled materials. Future research will focus on testing specimens derived from agricultural waste to assess their viability as sustainable insulation materials, contributing to energy-efficient building solutions.